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航空学院青年学术论坛第137讲 美国乔治华盛顿大学 梁春雷 教授 报告会(两场报告)
2019-02-24 09:24   审核人:

 

报告人:Prof. Chunlei Liang (梁春雷) The George Washington University

报告人简介:Dr. Chunlei Liang is an Associate Professor of Engineering and Applied Science at The George Washington University. He is an editorial board member of Computers & Fluids, an Elsevier Journal and an Associate Fellow of the American Institute of Aeronautics and Astronautics (AIAA). Prof. Liang received a Young Investigator Program award from the Office of Naval Research in 2014 and a CAREER award from the US National Science Foundation in 2016.

报告一: High-order Spectral Difference Method for Studying Rotary Wing Aerodynamics and Thermal Convection and Magneto-hydrodynamics for the Sun

时间:2019年2月26日 上午9:00-10:00

地点:航空楼A706

摘要:Two recent advancements of high-order spectral difference (SD) method for computational fluid dynamics on unstructured meshes will be presented. The first progress is our contribution to a new curved sliding-mesh approach to the SD method for simulating rotary wing aerodynamics. The second elevation of the SD method is our recent successful design of a massively parallel code, namely CHORUS, for predicting thermal convection in the Sun. Recently, we have also built a simulation capability for predicting magneto-hydrodynamics of the Sun.

 

 

报告二:A High-order Sliding and Deforming Spectral Difference Method for Exascale Simulations of Turbulent Flows

时间:2019年2月28日 上午9:00-10:00

地点:航空楼A706

摘要:I will present a novel high-order sliding and deforming spectral difference (SD^2) method for solving compressible Navier-Stokes equations on unstructured quadrilateral grids. The SD^2 method is an extension of the sliding-mesh spectral difference method (Zhang & Liang, 2015, J. Computational Physics) to coupled rotating and deforming domains. Through a simple sliding-mesh interface, the SD^2 method mitigates large grid distortion which is often resulted from rotating wall boundaries. Meanwhile, the SD^2 algorithm adopts an arbitrary Lagrangian-Eulerian framework that can handle large-amplitude translational motions of grid points on deforming domains. This new SD^2 solver is verified by using several benchmark flow problems able to demonstrate optimal orders of accuracy in space. The SD^2 method is efficient and robust for all our test problems and is expected to be a competitive algorithm for simulating turbulent flows of wind turbines by using exascale computers in the near future.

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